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Chinese medical journal · Jan 2014
Review Meta AnalysisPerformance of K-ras mutation analysis plus endoscopic ultrasound-guided fine-needle aspiration for differentiating diagnosis of pancreatic solid mass: a meta-analysis.
- Ying Xu, Duanmin Hu, Qi Zhu, and Yunwei Sun.
- Department of Gastroenterology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China; Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200092, China.
- Chin. Med. J. 2014 Jan 1; 127 (18): 329633013296-301.
BackgroundDifficulties persist in differentiating pancreatic ductal adenocarcinomas (PDAC) from pancreatic inflammatory masses (PIM). Auxiliary diagnostic techniques which enhance the endoscopic ultrasound-guided fine-needle aspiration (EUS-FNA) diagnostic yield have been attempted, for example, K-ras mutation analysis. We aimed to evaluate the accuracy of K-ras mutation analysis combined with EUS-FNA for the differential diagnosis of PDAC and PIM by pooling data of existing trials.MethodsWe systematically searched the Medline, PubMed, Web of Science, Embase, and Cochrane Central Trials databases for relevant published studies. Meta-analysis was performed. Pooling was conducted in fixed-effect model or random-effect model.ResultsIn total eight studies, with 696 cases of PDAC and 138 cases of PIM, met our inclusion criteria. The pooled sensitivity, specificity, positive likely ratio and negative likely ratio of K-ras mutation analysis combined with cytopathology for diagnosis of PDAC versus PIM were 90%, 95%, 13.45, and 0.13, respectively. Especially, among total 123 patients whose EUS-FNA results were inconclusive or negative, fifty-nine had K-ras mutations and were finally diagnosed with PDAC (48%, 59/123). Publication bias was not present.ConclusionsCombining K-ras mutation analysis with routine cytology moderately improves the ability of EUS-FNA to differentially diagnose between PDAC and PIM, especially for patients with suspected PDAC yet inconclusive EUS-FNA findings, and may prove to be a valuable supplemental method to EUS-FNA.
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